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--- |
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base_model: moro01525/T5_FineTuning |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: T5_FineTuning |
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results: [] |
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--- |
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# T5_FineTuning |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8659 |
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## Model description |
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The model is specialized on Text2Text Generation, in particular the model receives an input like "Ingredients: ingredient1, ingredient2, ..." (containing a list of ingredients) and generates a recipe |
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## Training and evaluation data |
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This model is trained using [**these**](https://www.kaggle.com/datasets/shuyangli94/food-com-recipes-and-user-interactions) datasets |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 55 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.9318 | 0.1818 | 1500 | 0.8757 | |
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| 0.9498 | 0.3636 | 3000 | 0.8712 | |
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| 0.9157 | 0.5455 | 4500 | 0.8683 | |
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| 0.9177 | 0.7273 | 6000 | 0.8672 | |
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| 0.9295 | 0.9091 | 7500 | 0.8659 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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